A consultant configured the AI-driven lead scoring model for a software company with a threshold tuned to flag only the top 5 percent of leads as high-priority. Sales leadership complains that many strong, ready-to-buy leads are being scored as low-priority and going unworked, even though the few leads that are flagged do convert well. What should the consultant recommend?
Select an answer to reveal the explanation.
Short Explanation
Picture a net set to catch only the very biggest fish, and it works great for those, but plenty of good-sized fish worth keeping are slipping right through the gaps. That is what a threshold set too tight does: the leads it does flag convert well, but too many other strong, ready-to-buy leads are falling just below the cutoff and never get worked. Making the net even smaller would only let more good ones through. Leaving the net as-is and asking the crew to manually check everything that slips past just piles extra work onto people who are already busy, without fixing the net itself. And getting rid of the net altogether throws away a signal that is mostly working, just calibrated too narrowly. The right move is to widen the opening a bit, accepting that the average quality of what gets caught may dip slightly, in exchange for catching far more of the good leads that were being missed.
Full Explanation
The correct answer is D. The complaint describes a threshold tuned too tightly, so it catches a small set of leads that convert well but misses many other strong leads that fall just outside that narrow band. Widening the threshold so more leads qualify as high-priority will surface those missed opportunities, even though the average conversion rate among flagged leads may dip slightly as a result. That trade-off is appropriate because the business problem is under-coverage, not poor precision. Option A is incorrect because tightening the threshold further would flag an even smaller set of leads, worsening the exact problem leadership is reporting. Option B is incorrect because it leaves the threshold's coverage gap unaddressed and simply adds a full manual review burden on top of sellers' existing workload, which does not scale and does not fix the underlying scoring configuration. Option C is incorrect because removing scoring entirely discards a working signal and reverts the team to unprioritized, first-in-first-out lead handling, which is a worse starting point than a threshold that only needs adjustment. The right fix is to recalibrate the threshold, not to abandon or manually patch around it.